There is increasing interest in the detection of human skin tones in digital images. Skin tone detection may be used, for example, to assist in facial detection and body detection. In the prior art various skin tone detection techniques have been implemented using expensive Digital Signal Processors (DSPs) or computers to identify skin tones in digital images using complicated optimal solution mathematical algorithms to identify skin tones and perform various image analysis processes. However, these approaches based on optimal solution image processing algorithms typically require substantial computational resources and are too expensive to be integrated into high-volume consumer products.
There is interest in implementing skin tone detection in digital cameras having a Complementary Metal Oxide Semiconductor (CMOS) image sensor. CMOS image sensors typically generate pixel data in a color space, such as the Red (R), Green (G), and Blue (B) color space. One conventional approach in CMOS image sensors is to convert the RGB color space into a UV chrominance space and then perform skin tone analysis in the UV space. For example, the research paper, “Real Time Skin-Region Detection with a Single-Chip Digital Camera”, in Proc. IEEE Intl. Conf. Image Processing, Thessaloniki, Greece, October 2001, describes a CMOS image sensor having a massively parallel embedded processor that implements skin tone detection in which R, G, B color values are transformed to U, V chrominance components (a UV color space) to perform skin tone detection.
However, the conventional approach to achieving an integrated skin tone detection capability in a CMOS image sensor has several drawbacks. One problem with UV based skin detection approaches is that it still requires more computing power than desired, due to the need to perform mathematical division operations to transform the RGB space into the UV space. Another problem is that performing skin tone detection in a UV space may make the skin tone detection accuracy dependent on lighting conditions. That is, when the same skin surface is lit with different illuminants the UV components of the captured image will vary, which in turn may cause errors in the skin tone detection algorithm. This is exacerbated by the problems in the prior art in implementing a low-cost noise filtering to eliminate false skin detection.
Therefore in light of the previously described problems what is desired is a new apparatus, system, and method to implement skin tone detection in CMOS image sensors.